OBJECTIVES: To develop a novel metric to evaluate the potential value of individualized care using traditional clinical trial data to prioritize patient centered outcomes research (PCOR). METHODS: Assume a head to head trial of 2 treatments (A and B), patients are randomly assigned to either treatment and QA and QB are outcomes obtained. The joint distribution (QAB) is not available as patients can only be assigned to one treatment. However, the marginal distributions of QA and QB, as obtained in a standard clinical trial, represent a plausible range of heterogeneous treatment effects. The extent of these marginal distributions can be used to form a Jointness-Box (JB) bounding an expected range of individual potential outcomes. Graphically, in a plot of QA vs. QB , where the 45-degree line represents the locus of equality, the JB represents the area enveloping the anticipated joint distribution of QA and QB. In our development, we examine conditions of JB dominance i.e. if the entire box is above or below the 45 degree line, and JB area i.e. proportion of the JB that falls above the 45 degree line. We used bootstrap methods, ordered statistics and percentile cutoffs to examine the likelihood of JB dominance, and confidence intervals for JB area across a range of starting assumptions and distributions. RESULTS: We found JB dominance is negatively correlated with the value of PCOR. The JB area vs. PCOR is concave shaped with maximal PCOR when JB area = 0.5. Simulation analysis indicates that for normally distributed trial outcomes, JB estimates are conservative in terms of inference about heterogeneity, and exhibit maximal accuracy when JB area = 0.5. CONCLUSIONS: The JB metric developed allows analysts and decision makers to intuitively understand the potential value and impact of exploring heterogeneity within a PCOR context.